In practice, this means OFFA encourages institutions to ensure that students from non-traditional backgrounds are successful following enrolment. Since students from under-represented groups are more likely to drop out of their studies, there should be a focus on retention – still a significant problem for the UK HE sector. Latest Higher Education Statistics Agency (HESA) data shows that, last year, more than 29,000 full-time students (7.4% of the intake) were no longer in higher education after 12 months.

Latest HESA data shows that, last year, more than 29,000 full-time students were no longer in higher education after 12 months.

Boosting retention is an area where learning analytics could have a big part to play in supporting fair access. Evidence from around the world shows that effective use of insights from learning analytics can be used to achieve statistically significant increases in retention.

There are two main ways that learning analytics can help power universities’ efforts in these areas:

1. Identification and intervention

Firstly, analytics are a powerful tool for identifying students at risk. Learning analytics systems draw data from across an institution into a single learning records warehouse. This might include usage data from the library and the virtual learning environment, as well as attendance records and grade data.

analytics are a powerful tool for identifying students at risk

A learning analytics processor then compares data on individual learners with current and historical data to identify any students who might be at risk of dropping out, or not meeting their full academic potential. Research has shown that the predictive models used are generally reliable – in one case correctly predicting three out of every four students not progressing to the next academic year.

Interventions can then be put in place to support the students identified. This might be as simple as informing students that they are at risk, or might involve prompting tutors to communicate with students to discuss how they can best be supported.

2. Evaluation

Secondly, because data on student engagement with learning can be monitored in near real time, the effectiveness of interventions with students can be quickly assessed (and, if necessary, adapted) without having to wait for final examination and/or assessment results.

the effectiveness of interventions with students can be quickly assessed

At a time when there is increasing focus on the efficacy of spending on access and student success, this can help institutions to review and demonstrate the effectiveness of their student support. We expect this will inform improvements to the guidance and support available across the board to whole cohorts of students, as well as interventions offered to individual students at risk.

Access agreements

In addition to the benefits of increasing retention, we think that effective use of learning analytics data insights could also become part of institutions’ commitment to OFFA in their access agreements.

learning analytics data insights could also become part of institutions’ commitment to OFFA in their access agreements.

Our analysis of 2017/18 access agreements found that 14 institutions explicitly mention learning analytics. Buckinghamshire New University, for example, highlights that it “intends to introduce learning analytics to inform the support, learning, engagement, retention and success of its students” as part of its efforts to establish a stronger culture and practice of data usage across the institution. Exeter University’s access agreement states that it is “developing effective learning analytics tools to enable both students and tutors to monitor performance more effectively and identify strategies to improve”.

We also believe that there is a compelling case for some of the funds that institutions are spending on learning analytics to be designated as “access agreement expenditure”, where institutions can demonstrate that learning analytics is part of their strategy for improving the outcomes of under-represented and disadvantaged groups.

What next?

We are encouraging institutions we are working with to consider how learning analytics data might feed into the development of their annual access agreement with OFFA – as well as more general efforts to promote fair access and student success within their institution.

Share this

About the author

Chief innovation officer, Jisc

Phil leads and continuously develops a world class futures team: a group of experts with the capacity to identify, shape and exploit opportunities for new, digitally enabled, ways of working. As with all of Jisc, the focus of their activity is creating the greatest benefit for the sectors we serve.

Joel Mullan

Former senior executive adviser, Jisc

Joel left Jisc in February 2018. Most recently, he worked with the chief executive and members of the Jisc executive group, providing strategic and operational advice and support. He also contributed to the development and implementation of the Jisc group strategy.